The design of cutting tools, and their utilization in machining materials under various cutting conditions, has traditionally relied upon a combination of experience and empirical data. Disadvantageously, this approach is very time consuming, costly, and difficult to apply. With the introduction of new cutting tool materials such as ceramics and cermets, there exisits in the prior art an even greater demand for chip control, tool reliability and high performance in view of the complex cutting conditions under which these new tools are subjected.
In conventional product design cycles, the cutting-tool design engineer usually begins the design of a new tool with a specific product objective such as: (i) requirement to cut a specific material, or (ii) utilization of a particular cutting speed, feed or depth of cut in a lathe, mill, or other cutting machine. Based on previous tool design experience, the designer selects the tool material which usually consists of a hard substrate such as WC-Co with suitable coatings applied to the surface for further protection against tool wear.
The chipbreaker geometry of the cutting tool surface is specified based on tool material and machining conditions, and a prototype tool is constructed in accordance with this geometry and the design specifications. Conventional machinability tests for evaluating the performance of the tool typically consist of applying the prototype tool insert to the specified workpiece material over a range of machining conditions such as cutting speed, depth of cut, and feed rate. As the tool insert is applied to the workpiece, chips are formed with characteristics particular to each cutting condition. These chips are preferably used to construct a chip-board matrix depicting the chip geometries as a function of range of speeds and feeds for a selected workpiece material. The chip board is then used to determine the optimal range of cutting conditions for the newly designed insert based upon chip morphology, chip microstructure, machine dynamic response (such as chatter, noise, and power consumption), and wear characteristics of the cutting tool. A desired chip geometry results when the excess workpiece material is cut into small, discrete fragments curled substantially in the shape of the numeral `6`. Long or `stringy` chips are considered unacceptable since they reduce the performance of unmanned machining centers and produce a safety hazard to machine-tool operators.
Disadvantageously, the prototypical tool design procedure of the prior art typically does not meet its desired performance objectives in the first several iterations of this design and testing process, thereby causing the designer to repeat the procedure until a suitable level of performance is attained. This is a time-consuming process, further delayed by the difficulty in manufacturing new prototype tool inserts. For example, prototype cutting tools based on the WC-Co material mentioned above are manufactured by powder metallurgy methods but require a complex and expensive punch-and-die set for cold pressing the powders. Furthermore, redesign or rework in the tool design or manufacturing operations lead to further delays and lead-time in the development of new products.
Another aspect of tool development in the prior art is the unavailability of results from previous machinability studies for use in evaluating tool response. For example, a characteristic of the cutting tool industry is that information accumulated by individual tool designers based on their experience with diverse machining operations is typically not made available to the tool industry since the industry lacks a mechanism for collecting and disseminating such information. Consequently, there exists in the industry a need to consolidate the prior information gained in machinability tests, and to integrate this data into a system whereby tool design experience can be stored and easily accessed in a computerized data base.
While the cutting tool industry has historically designed new tools by repeatedly manufacturing and testing tool prototypes as discussed above, the prior art has recently used mathematical models of the metal-cutting process to predict the shear plane angle, outgoing chip thickness, and forces exerted on the tool insert. Examples of such predictive models are discussed by E. M. Trent in Metal Cutting, Butterworths, 1984; M. C. Shaw in Metal Cutting Principles, MIT Press, 1968; and by N. N. Zorev in Metal Cutting Mechanics, Pergamon Press, 1966. Most of these models incorporate an elastic-plastic material model, but with no temperature or rate effects included. Good agreement with experimental results can be achieved with these models for the shear plane angle related to the rake angle and chip thickness. However, these models fail to adequately describe the process in that they do not account for friction along the tool-chip interface, strain hardening of the workpiece, temperature and rate-dependent properties of the workpiece, and the mechanics of separation of the chip from the workpiece. Later modifications to these models are disclosed by Boothroyd et al. in "Effects of Strain Rate and Temperature in orthogonal metal cutting," J. of Mechanical Eng. Science, 1966 and Stevenson et al.
As a further modification, Strenkowski and Carroll in "A finite element model of orthogonal metal cutting," ASME Journal of Engineering for Industry (1985) and Usui in "Progress of predictive theories in metal cutting," JSME International Journal (1988) discuss finite element models of the cutting process, The simulations with these models occur under orthogonal cutting conditions so that plane theories of deformation can be applied, and require machinability data as input (such as chip-shape and flow lines). However, these models are only applicable at very low cutting speeds. Additionally, Benton et al. in "An adiabatic heating finite element analysis of metal cutting," MIT (1986), Iwata et al. in "Process modeling of orthogonal cutting by the rigid-plastic finite element method," ASME J. of Engineering Materials and Technology (1984), and Strenkowski, supra, illustrate the separation of the chip from the workpiece by a release of certain nodes in the finite element mesh as the chip slides across the surface of the tool. Lee et al. in "Material modeling and high-speed machining processes," Advanced Machining Research Program Annual Report, General Electric Co., Schenectady, N.Y. (1982) illustrate the separation by the `death` of certain elements by removing them from following iterations of the solution procedure. Analyses using rigid-plastic material properties for the chip at low cutting speeds under isothermal conditions were also performed as disclosed in Iwata et al., supra and Lee et al., supra. Iwata's model included a fracture prediction of the chip from the workpiece, based on the ductile fracture strain of the steel under consideration.
Strenkowski, supra, and Strenkowski and Mitchum in "An improved finite element model of orthogonal metal cutting," Manufacturing Technology Review-NAMRC XV (1987) illustrate an updated Lagrangian approach for the investigation of the cutting process. The material model of the workpiece was thermo-elasto-plastic with friction at the interface of the tool and chip. A parting-line criterion was used for the separation of the chip from the workpiece, and a critical strain measure was implemented to determine when the chip would separate. Large volumes of the workpiece and tool were modeled in this approach, thus resulting in prohibitively large computation times.
Benton et al., supra, abandoned the concept of a strain-to-failure at the debonding of the chip from the workpiece in favor of a release criterion based on the distance of the workpiece from the tip of the cutting tool.
In summary, the prior art in the design and selection of cutting tools has lacked an integrated system for readily accessing machining data and tool design experience from a database, for comprehensive and accurate modelling of the physical phenomena in cutting operations, and for adaptively evaluating tool response and chip-flow simulations.